Geographical data storage assignment based on ontological relevancy

• US 10,264,090 B2
• Filed: 02/27/2014
• Issued: 04/16/2019
• Est. Priority Date: 02/27/2013
• Status: Active Grant

• Current Assignee: Pavlov Media, Inc. (Wavelength Corp.)
• Original Assignee: Pavlov Media, Inc. (Wavelength Corp.)
• Inventors: Wyatt, Bartow, Scifres, Mark
• Primary Examiner(s): Ly, Anh
• Application Number:
  US14/192,378
• Publication Number:
  US 20140244648A1
• Time in Patent Office: 1,874 Days
• Field of Search: 707737, 707749, 707723, 707E17044, 707E17089, 709218, 709203
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9574 of access to content, e.g. by caching
• CPC Class Codes: H04L 67/1097 for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
• CPC Class Codes: H04L 67/568 Storing data temporarily at an intermediate stage, e.g. caching

Abstract

System and method for distributing channelized content to a plurality of cohesive local networks. The channelized content is aggregated at a remote central processor with associated storage according to ontological relevancy, and then distributed over a network such as the internet to the local networks. The consumers connected to the respective local networks receive that channelized data with low latency and improved data rates.

Claims

1. A method for distributing channelized content to a plurality of cohesive local networks to provide the content to a client device connected to a local network at extremely fast data rates without at least some of the delays and latency associated with conventional internet downloads by:

calculating, in a computer, relevance of a content request received across a computer network from a client device based on a geographical location from which the request originated with respect to a channel of previously-aggregated content,

calculating, in a computer, the content request based on socio-economic relevance of the content request with respect to a channel of previously-aggregated content,

developing from one or more of the channels of previously-aggregated content groups of requested content to be delivered across a computer network based on the calculating steps in anticipation of future content requests received across the computer network from client devices located in the same geographical location,

delivering through a computer network at least a portion of at least one of the groups of content to one or more connected to the computer network based on the geographical and socio-economic relevancy,

storing as local content on at least one of the cohesive local networks at least a portion of the delivered groups of content, and

delivering to a client device from a cohesive local network associated with that client device and connected locally thereto via a high speed data link at least a portion of the delivered groups of content stored as local content on the associated cohesive local network to thereby provide that content to the consumer at an extremely fast data rate.

2. The method of claim 1 wherein the cohesive local networks are geographically cohesive.

3. The method of claim 1 wherein the cohesive local networks are edge networks.

4. The method of claim 1 wherein channelized content comprises content that has previously been aggregated as likely to be requested by a group of users within a cohesive edge network.

5. The method of claim 1 wherein the cohesive local network includes a network appliance.

6. The method of claim 1 wherein the content request is associated with a network appliance.

7. The method of claim 6 further comprising the step of calculating demographic information associated with the network appliance.

8. The method of claim 7 wherein the demographic information comprises historical data developed based on prior requests.

9. The method of claim 8 further comprising the step of developing metadata representative of the historical data.

10. The method of claim 9 further comprising the step of associating the metadata back to the network appliance that generated the content request.

11. The method of claim 9 wherein the metadata evolves as additional content requests are processed.

12. The method of claim 11 further comprising the step of developing, based on the metadata, figures of merit regarding relevancy of a content request to existing channels.

13. The method of claim 1 wherein the computer network includes a regional network appliance.

14. The method of claim 1 wherein metadata associated with a group of content is blended with cohesive local network metadata.